AI & Deep Learning
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Date: Wednesday, Aug 14, 2019
Time: 9:00am – 10:00am PT
Duration: 1 hour

Investment management firms seek alternative datasets, such as consumer transactions, logistics information, and employment trends, to improve trading strategies with an informational edge. This opens up new potential use cases that could allow investment management firms to analyze digital residue to value assets more accurately, on a near real-time basis, to visualize anomalies that may represent hidden portfolio risk, and to enhance investment analysis and capital market research. Yet the scale of these alternate data streams, often measured in billions of rows, has traditionally been too time-consuming or costly to examine.

In this webinar you will learn:
  • How GPU accelerated analytics can help provide unique and timely insights into investment opportunities.
  • About the ability to bring together nontraditional datasets in a quick exploratory matter.
  • To switch seamlessly between visual exploration of a dataset and deeper experimentation using data science tools, all powered by GPUs.

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DGX Station Datasheet

Get a quick low-down and technical specs for the DGX Station.
DGX Station Whitepaper

Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
DGX Station Whitepaper

Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.

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Speakers

Venkat Krishnamurthy

VP of Product Management , OmniSci

Venkat heads up Product Management at OmniSci. He joined OmniSci from the CTO office at Cray, the supercomputing pioneer, where he was responsible for leading Cray’s push into Analytics and AI. Earlier, he was Senior Director at YarcData, a pioneering graph analytics startup, where he bootstrapped product and data science/engineering teams. Prior to YarcData, he was a Director of Product Management at Oracle, where he led the launch of the Oracle Financial Services Data Platform, and earlier spent several years at Goldman Sachs, where he led one of the earliest successful projects utilizing machine learning in Operational Risk incident classification. Venkat is a graduate of Carnegie Mellon University and the Indian Institute of Technology Chennai, and also a certified Financial Risk Manager.

Patrick Hogan

Senior Solutions Architect, NVIDIA

Patrick Hogan is a Senior Solutions Architect at NVIDIA who also manages the Financial Services Solution Architect team for North America. His focus includes GPU acceleration in Data Analytics, Machine Learning, as well as Deep Learning. Patrick’s interest in Financial Services came from supporting clients while at Sun Microsystems, however, spent the majority of his career working for financial firms. Over his 18 years in the Industry, he managed technology for Equities, Program Trading, and Derivatives application environments. It was his passion for mathematics and data analysis that led to the Director level position in Hedge Fund Administration and designing complex Enterprise Data Warehouses for self-service reporting and trade reconciliation. Throughout Patrick’s career, he’s never strayed far from his roots in software development which started at a firm that designed a software/hardware platform for printed circuit board design.

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Date & Time: Wednesday, April 22, 2018